In a Magnetic Resonance Imaging (MRI) system, a receiving coil detects magnetic resonance properties of a sample of material under study (e.g., a patient's body). The receiving coil outputs a resonance signal that varies greatly in amplitude in very short bursts. To obtain this signal, the sample has to be subjected to various cycles of magnetic fields and a burst of radio energy, after which, the receiving coil receives a burst of return radio energy. This is repeated many times for each image, each time using a slightly different magnetic field, called the phase-encoding gradient. The phase-encoding gradient makes each physical part of the sample radiate a slightly different signal so that a computer can determine the correspondence between a portion of the signal and the physical part of the sample.
The receiving coil typically detects one or more nuclear magnetic resonance (NMR) signals generated by a volume of the sample material. The dimensions of the sample volume may vary depending on system requirements and on the needs of the system operator. For example, to generate a two-dimensional (2D) MRI image, a slice having a width of about five (5) millimeters may be sufficient. On the other hand, if a three-dimensional (3D) image is desired, it may be necessary to scan a substantially larger volume, referred to as a slab volume, such as a slab volume fifty (50) millimeters wide, for example.
Each of the signal bursts of return radio energy corresponds to a unique cycle corresponding to a different phase encoding gradient. These signals are converted to digital form using an analog-to-digital converter (ADC), and stored in a matrix, with the corresponding phase encoding varying by row, and time (from beginning to the end of the signal) varying by column. Then mathematics is performed on the rows and columns to transform the rows and columns of signal data to rows and columns of an image, like the pixels of a computer monitor, as is known in the art.
The amplitude for each signal corresponding to a given phase encoding level can vary over a very wide range. However, that range normally varies from one phase encoding level to the next; the range tends to swell and then taper off as the phase-encoding level is varied. The signal range also varies with slice thickness, pulse repetition time, echo time, sample material size, sample material fat content, the type of receiver coil, etc., but these remain constant during a given imaging sequence.
In an MRI system, the need to process signals having widely varying ranges poses particular challenges. One such difficulty is related to the problem of quantization noise. Quantization noise is a type of noise that results from error in the conversion of an analog signal to a digital form by an ADC. Digital signals have discrete steps in amplitude, while analog signals can be smooth. So while an analog signal may rise or fall like a ramp, a digital signal rises or falls in discrete steps, like a staircase. When a smooth analog signal is transformed into a signal with steps, a certain amount of error results because portions of the analog signal between the steps must be converted to a signal that skips from one step to another rather than smoothly varying between them. This makes a smooth analog signal look like a noisy analog signal. To eliminate this type of additional noise, designers try to use ADCs with a lot of steps; the more steps, the finer the graininess caused by jumping between steps. However, there are practical reasons for using the ADC with the smallest number of steps possible. One is that using more steps can make the downstream equipment that uses the digital signal very expensive because each signal level must be encoded by a large amount of data.
The design of signal conditioning systems involving the conversion of analog signals to digital form invariably confronts the issue of quantization noise, although in most cases, it is just a routine step in the design process. But in some kinds of signal analysis systems, including MRI systems, quantization noise is not so easily addressed. This is because of a characteristic of certain signals known as “dynamic range,” which refers to how much variation the signal exhibits in its amplitude. A signal with a large dynamic range contains useful data at portions that are high in amplitude and at portions that are low in amplitude. In MRI systems, this problem is acute because useful information is contained in the signal all the way down to the point at which its amplitude approaches zero.
The problem with handling such signals arises because of the large number of ADC steps required when a signal varies greatly in amplitude. Ideally, the designer wants as many steps as possible to minimize the quantization noise. However, the amount of noise in the original analog signal places a lower limit on how much a greater number of steps will ultimately increase the quality of the digital signal. It makes no sense to add more steps to the ADC when the steps of the ADC are already much smaller than noise in the original analog signal. Trying to reduce the magnitude of a very small quantization noise added to a signal that already has a much higher noise level, is wasteful because it takes a lot of computing power to handle a digital signal with a lot of amplitude steps. Therefore, the best approach is to select an ADC whose step size (least significant bit) is smaller than the amplitude of the noise part of the original analog signal.
One common problem frequently encountered in the field of MRI imaging is related to the fact that the performance of many receivers is optimal only for signals having an amplitude within a specified range. For example, a receiver that is configured and calibrated to process a signal or a set of signals having a specified dynamic range may fail to produce useful results when used to measure a signal with, say, a much greater dynamic range. Accordingly, in MRI systems, it is important to ensure that a receiver used to detect and process a resonance signal having a respective amplitude is configured and calibrated to be able to handle a signal of such amplitude. The maximum signal amplitude relative to the noise that a particular receiver experiences is referred to as the receiver's “dynamic range requirement.”
The dynamic range requirement of an MRI receiver is proportional to the NMR signal, which is itself proportional to the size of the imaging volume (or to the sample volume within the imaging volume). This is due to the fact that at a certain point in time, all the excited nuclei within the imaging volume (or in the sample volume within the imaging volume) are in phase and generate a signal that is the sum of all the nuclei. For example, as is discussed above, generating a 3D image generally requires a larger imaging volume or sampling volume than is needed for 2D imaging. Consequently, the dynamic range requirement tends to be higher when a receiver is used to perform 3D imaging.
One practice common in the MRI field is the use of multiple coils to detect a resonance signal from a volume under study. In one well-known implementation, an array consisting of multiple coils allows a physician to perform a full-body scan of a patient. When the volume is divided into sub-volumes with a plurality of coils, the dynamic range requirement of the receiver is reduced. If the receiver comprises multiple coils each of which is coupled to a channel in the receiver, increasing the number of coils can reduce the dynamic range requirement for each channel.
Some existing MRI systems use coil arrays comprising coils that are decoupled from each other. Such coil arrays include phased array coils and quadrature coils, for example. Coils of an array may be decoupled due to their geometry (angle and/or distance between coils) and other methods, as is known in the art. Coil arrays may be used to cover a large imaging volume, dividing the large imaging volume into smaller sub-volumes. Some or all of the sub-volumes may overlap. Small coils usually have a higher Q and higher filling factor than larger coils, enabling a substantial improvement in image quality, especially over a large imaging volume. In addition, the smaller coils in the array may be coupled to pre-amplifiers and receivers that are better able to accommodate the required dynamic range of the signals detected by the receiving coil.
The use of multiple coil arrays in an MRI system enables the operator some ability to control the dynamic range requirement for each coil in the array. However, it is still typically the case for each receiver in a coil array system to be configured and calibrated for signals having a specified dynamic range. Therefore, the use of coil arrays in existing MRI systems reduces, but does not eliminate, the dynamic range requirement problem.